Source-receiver compression scheme for full-waveform seismic inversion

Geophysics ◽  
2011 ◽  
Vol 76 (4) ◽  
pp. R95-R108 ◽  
Author(s):  
T. M. Habashy ◽  
A. Abubakar ◽  
G. Pan ◽  
A. Belani
Keyword(s):  
Seismic Inversion ◽  
Computational Time ◽  
Weighted Sums ◽  
Inversion Method ◽  
Elastic Model ◽  
Memory Usage ◽  
Compression Scheme ◽  
Decomposition Approach ◽  
Redundant Data ◽  
Full Waveform

We have developed a source-receiver compression approach for reducing the computational time and memory usage of the acoustic and elastic full-waveform inversions. By detecting and quantifying the extent of redundancy in the data, we assembled a reduced set of simultaneous sources and receivers that are weighted sums of the physical sources and receivers used in the survey. Because the numbers of these simultaneous sources and receivers could be significantly less than those of the physical sources and receivers, the computational time and memory usage of any gradient-type inversion method such as steepest descent, nonlinear conjugate gradient, contrast-source inversion, and quasi-Newton methods could be reduced. The scheme is based on decomposing the data into their principal components using a singular-value decomposition approach, and the data reduction is done through the elimination of the small eigenvalues. Consequently, this would suppress the effect of noise in the data. Moreover, taking advantage of the redundancy in the data, this compression scheme effectively stacks the redundant data, resulting in an increased signal-to-noise ratio. For demonstration of the concept, we produced inversion results for the 2D acoustic Marmousi and BP models for surface measurements and an elastic model for crosswell measurements. We found that this approach has the potential to significantly reduce computational time and memory usage of the Gauss-Newton method by 1–2 orders of magnitude.

Comparison of source-independent methods of elastic waveform inversion

Geophysics ◽  
2006 ◽  
Vol 71 (6) ◽  
pp. R91-R100 ◽  
Author(s):  
Kun Xu ◽  
Stewart A. Greenhalgh ◽  
MiaoYue Wang
Keyword(s):  
Elastic Wave ◽  
Frequency Domain ◽  
Numerical Experiments ◽  
Random Noise ◽  
Waveform Inversion ◽  
Seismic Inversion ◽  
Inversion Method ◽  
Practical Procedure ◽  
Wave Inversion ◽  
Full Waveform

In this paper, we investigate several source-independent methods of nonlinear full-waveform inversion of multicomponent elastic-wave data. This includes iterative estimation of source signature (IES), standard trace normalization (STN), and average trace normalization (ATN) inversion methods. All are based on the finite-element method in the frequency domain. One synthetic elastic crosshole model is used to compare the recovered images with all these methods as well as the known source signature (KSS) inversion method. The numerical experiments show that the IES method is superior to both STN and ATN methods in two-component, elastic-wave inversion in the frequency domain when the source signature is unknown. The STN and ATN methods have limitations associated with near-zero amplitudes (or polarity reversals) in traces from one of the components, which destroy the energy balance in the normalized traces and cause a loss of frequency information. But the ATN method is somewhat superior to the STN method in suppressing random noise and improving stability, as the developed formulas and the numerical experiments show. We suggest the IES method as a practical procedure for multicomponent seismic inversion.

scholarly journals Optimal coding of blended seismic sources for 2D full waveform inversion in time

2018 ◽  
Vol 8 (2) ◽  
Author(s):  
Katherine Flórez ◽  
Sergio Alberto Abreo Carrillo ◽  
Ana Beatriz Ramírez Silva
Keyword(s):  
Waveform Inversion ◽  
Velocity Model ◽  
Computational Time ◽  
Inversion Method ◽  
Single Shot ◽  
Full Waveform Inversion ◽  
Velocity Models ◽  
Full Waveform ◽  
Seismic Image ◽  
Blended Data

Full Waveform Inversion (FWI) schemes are gradually becoming more common in the oil and gas industry, as a new tool for studying complex geological zones, based on their reliability for estimating velocity models. FWI is a non-linear inversion method that iteratively estimates subsurface characteristics such as seismic velocity, starting from an initial velocity model and the preconditioned data acquired. Blended sources have been used in marine seismic acquisitions to reduce acquisition costs, reducing the number of times that the vessel needs to cross the exploration delineation trajectory. When blended or simultaneous without previous de-blending or separation, stage data are used in the reconstruction of the velocity model with the FWI method, and the computational time is reduced. However, blended data implies overlapping single shot-gathers, producing interference that affects the result of seismic approaches, such as FWI or seismic image migration. In this document, an encoding strategy is developed, which reduces the overlap areas within the blended data to improve the final velocity model with the FWI method.

scholarly journals Near surface reconstruction using the full waveform inversion method: a resolution analysis

2016 ◽  
pp. 487-499
Author(s):  
К.Г. Гадыльшин ◽  
Д.А. Неклюдов ◽  
И.Ю. Сильвестров
Keyword(s):  
Rayleigh Waves ◽  
Waveform Inversion ◽  
Observation System ◽  
Inversion Method ◽  
Elastic Model ◽  
Full Waveform Inversion ◽  
Elastic Parameters ◽  
Near Surface ◽  
Full Waveform ◽  
Resolution Analysis

Изучается влияние волны Рэлея на результат обращения полного волнового поля. Показано, что разрешающая способность борновского оператора выше в случае отсутствия рэлеевских волн в наблюдаемых данных. Предложен численный алгоритм, позволяющий анализировать влияние различных параметров обратной динамической задачи сейсмики на результат восстановления верхней части геологического разреза: геометрии системы наблюдений, частотного диапазона, параметризации упругой модели и др. В качестве демонстрационного примера показано, что для поверхностной системы наблюдений в задаче реконструкции макроскоростного строения среды наиболее приемлема параметризация упругой модели через скорости продольных и поперечных волн и плотность. The effect of the Rayleigh wave on full waveform inversion (FWI) is studied. It is shown that the Born operator resolution is better when the Rayleigh waves are not taken into account. A numerical algorithm to analyze the influence of different parameters of the inverse dynamical seismic problem (such as source/receiver geometry, frequency range, elastic model parametrization, etc.) on the near-surface geological section reconstruction is proposed. As a demonstrative example, we show that the best elastic parameters for macrovelocity reconstruction via FWI for a subsurface observation system are P- and S-velocities and density.

scholarly journals A direct inverse method for subsurface properties: The conceptual and practical benefit and added value in comparison with all current indirect methods, for example, amplitude-variation-with-offset and full-waveform inversion

2017 ◽  
Vol 5 (3) ◽  
pp. SL89-SL107 ◽  
Author(s):  
Arthur B. Weglein
Keyword(s):  
Success Rate ◽  
Waveform Inversion ◽  
Forward Problem ◽  
Inversion Method ◽  
Elastic Model ◽  
Full Waveform Inversion ◽  
Amplitude Variation ◽  
Indirect Methods ◽  
Amplitude Variation With Offset ◽  
Full Waveform

Direct inverse methods solve the problem of interest; in addition, they communicate whether the problem of interest is the problem that we (the seismic industry) need to be interested in. When a direct solution does not result in an improved drill success rate, we know that the problem we have chosen to solve is not the right problem — because the solution is direct and cannot be the issue. On the other hand, with an indirect method, if the result is not an improved drill success rate, then the issue can be either the chosen problem, or the particular choice within the plethora of indirect solution methods, or both. The inverse scattering series (ISS) is the only direct inversion method for a multidimensional subsurface. Solving a forward problem in an inverse sense is not equivalent to a direct inverse solution. All current methods for parameter estimation, e.g., amplitude-variation-with-offset and full-waveform inversion, are solving a forward problem in an inverse sense and are indirect inversion methods. The direct ISS method for determining earth material properties defines the precise data required and the algorithms that directly output earth mechanical properties. For an elastic model of the subsurface, the required data are a matrix of multicomponent data, and a complete set of shot records, with only primaries. With indirect methods, any data can be matched: one trace, one or several shot records, one component, multicomponent, with primaries only or primaries and multiples. Added to that are the innumerable choices of cost functions, generalized inverses, and local and global search engines. Direct and indirect parameter inversion are compared. The direct ISS method has more rapid convergence and a broader region of convergence. The difference in effectiveness increases as subsurface circumstances become more realistic and complex, in particular with band-limited noisy data.

scholarly journals Construction of Apple Leaf Diseases Identification Networks Based on Xception Fused by SE Module

2021 ◽  
Vol 11 (10) ◽  
pp. 4614
Author(s):  
Xiaofei Chao ◽  
Xiao Hu ◽  
Jingze Feng ◽  
Zhao Zhang ◽  
Meili Wang ◽  
...  
Keyword(s):  
Disease Control ◽  
Classification Accuracy ◽  
Mobile Terminal ◽  
Disease Classification ◽  
Memory Usage ◽  
Compression Scheme ◽  
Accurate Identification ◽  
Average Classification Accuracy ◽  
Network Compression ◽  
Control And Management

The fast and accurate identification of apple leaf diseases is beneficial for disease control and management of apple orchards. An improved network for apple leaf disease classification and a lightweight model for mobile terminal usage was designed in this paper. First, we proposed SE-DEEP block to fuse the Squeeze-and-Excitation (SE) module with the Xception network to get the SE_Xception network, where the SE module is inserted between the depth-wise convolution and point-wise convolution of the depth-wise separable convolution layer. Therefore, the feature channels from the lower layers could be directly weighted, which made the model more sensitive to the principal features of the classification task. Second, we designed a lightweight network, named SE_miniXception, by reducing the depth and width of SE_Xception. Experimental results show that the average classification accuracy of SE_Xception is 99.40%, which is 1.99% higher than Xception. The average classification accuracy of SE_miniXception is 97.01%, which is 1.60% and 1.22% higher than MobileNetV1 and ShuffleNet, respectively, while its number of parameters is less than those of MobileNet and ShuffleNet. The minimized network decreases the memory usage and FLOPs, and accelerates the recognition speed from 15 to 7 milliseconds per image. Our proposed SE-DEEP block provides a choice for improving network accuracy and our network compression scheme provides ideas to lightweight existing networks.

scholarly journals Application of an Improved Ultrasound Full-Waveform Inversion in Bone Quantitative Measurement

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 260
Author(s):  
Meng Suo ◽  
Dong Zhang ◽  
Yan Yang
Keyword(s):  
Nonlinear Equations ◽  
Waveform Inversion ◽  
Optimal Solution ◽  
Inversion Method ◽  
Full Waveform Inversion ◽  
Inversion Algorithm ◽  
Elastic Wave Equation ◽  
Full Waveform ◽  
Ultrasonic Propagation ◽  
Joint Velocity

Inspired by the large number of applications for symmetric nonlinear equations, an improved full waveform inversion algorithm is proposed in this paper in order to quantitatively measure the bone density and realize the early diagnosis of osteoporosis. The isotropic elastic wave equation is used to simulate ultrasonic propagation between bone and soft tissue, and the Gauss–Newton algorithm based on symmetric nonlinear equations is applied to solve the optimal solution in the inversion. In addition, the authors use several strategies including the frequency-grid multiscale method, the envelope inversion and the new joint velocity–density inversion to improve the result of conventional full-waveform inversion method. The effects of various inversion settings are also tested to find a balanced way of keeping good accuracy and high computational efficiency. Numerical inversion experiments showed that the improved full waveform inversion (FWI) method proposed in this paper shows superior inversion results as it can detect small velocity–density changes in bones, and the relative error of the numerical model is within 10%. This method can also avoid interference from small amounts of noise and satisfy the high precision requirements for quantitative ultrasound measurements of bone.

Target-oriented inversion using the Patched Green′s function method

Geophysics ◽  
2021 ◽  
pp. 1-77
Author(s):  
Danyelle da Silva ◽  
Edwin Fagua Duarte ◽  
Wagner Almeida ◽  
Mauro Ferreira ◽  
Francisco Alirio Moura ◽  
...  
Keyword(s):  
Condensed Matter ◽  
Waveform Inversion ◽  
Time Lapse ◽  
Velocity Model ◽  
Dyson Equation ◽  
Computational Time ◽  
Green Functions ◽  
Target Area ◽  
Computational Domain ◽  
Full Waveform

We have designed a target-oriented methodology to perform Full Waveform Inversion using a frequency-domain wave propagator based on the so-called Patched Green’s Function (PGF) technique. Originally developed in condensed matter physics to describe electronic waves in materials, the PGF technique is easily adaptable to the case of wave propagation in a spatially variable media in general. By dividing the entire computational domain into two sections, namely the target area and the outside target area, we calculate the Green Functions related to each section separately. The calculations related to the section outside the target are performed only once at the beginning of inversion, whereas the calculations in the target area are performed repeatedly for each iteration of the inversion process. With the Green Functions of the separate areas, we calculate the Green Functions of the two systems patched together through the application of a Recursive Dyson equation. By performing 2D and time-lapse experiments on the Marmousi model and a Brazilian Pre-salt velocity model, we demonstrate that the target-oriented PGF reduces the computational time of the inversion without compromising accuracy. In fact, when compared with conventional FWI results, the PGF-based calculations are identical but done in a fraction of the time.

scholarly journals Gas Saturated Sandstone Reservoir Modeling Using Bayesian Stochastic Seismic Inversion

2020 ◽  
Vol 5 (1) ◽  
pp. 25-31
Author(s):  
Rahmat Catur Wibowo ◽  
Ditha Arlinsky Ar ◽  
Suci Ariska ◽  
Muhammad Budisatya Wiranatanagara ◽  
Pradityo Riyadi
Keyword(s):  
Scale Up ◽  
Seismic Inversion ◽  
Well Logs ◽  
Reservoir Modeling ◽  
Inversion Method ◽  
Tight Sandstone ◽  
Stochastic Inversion ◽  
A Value ◽  
Sandstone Reservoir ◽  
Stochastic Seismic Inversion

This study has been done to map the distribution of gas saturated sandstone reservoir by using stochastic seismic inversion in the “X” field, Bonaparte basin. Bayesian stochastic inversion seismic method is an inversion method that utilizes the principle of geostatistics so that later it will get a better subsurface picture with high resolution. The stages in conducting this stochastic inversion technique are as follows, (i) sensitivity analysis, (ii) well to seismic tie, (iii) picking horizon, (iv) picking fault, (v) fault modeling, (vi) pillar gridding, ( vii) making time structure maps, (viii) scale up well logs, (ix) trend modeling, (x) variogram analysis, (xi) stochastic seismic inversion (SSI). In the process of well to seismic tie, statistical wavelets are used because they can produce good correlation values. Then, the stochastic seismic inversion results show that the reservoir in the study area is a reservoir with tight sandstone lithology which has a low porosity value and a value of High acoustic impedance ranging from 30,000 to 40,000 ft /s*g/cc.

Analysis of Elastic Machinery With Clearances

1973 ◽  
Vol 95 (3) ◽  
pp. 695-703 ◽  
Author(s):  
R. C. Winfrey ◽  
R. V. Anderson ◽  
C. W. Gnilka
Keyword(s):  
Computer Program ◽  
Valve Train ◽  
Computational Time ◽  
Elastic Model ◽  
Elastic Link

Previous work on the analysis of elastic link mechanisms has been enlarged upon so as to include the effect of intermittent separation and impact between members. A cam-driven valve train is used as an example to demonstrate the methods for analyzing an elastic machine with clearances. Also demonstrated is a method for bookkeeping, or keeping track of the various configurations which the machine can assume due to the clearances. The methods presented here are sufficiently general to be applied to a variety of machinery; however, a cam-driven valve train was selected as an example because (1) it could be represented by a relatively simple elastic model, thus reducing the size of the computer program, and (2) an essentially constant geometry could be assumed, thus saving considerable computational time.

Source-independent extended waveform inversion based on space-time source extension: Frequency-domain implementation

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R449-R461 ◽  
Author(s):  
Guanghui Huang ◽  
Rami Nammour ◽  
William W. Symes
Keyword(s):  
Source Function ◽  
Random Noise ◽  
A Priori ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Inversion Method ◽  
Target Velocity ◽  
Extended Source ◽  
Full Waveform ◽  
Time Variables

Source signature estimation from seismic data is a crucial ingredient for successful application of seismic migration and full-waveform inversion (FWI). If the starting velocity deviates from the target velocity, FWI method with on-the-fly source estimation may fail due to the cycle-skipping problem. We have developed a source-based extended waveform inversion method, by introducing additional parameters in the source function, to solve the FWI problem without the source signature as a priori. Specifically, we allow the point source function to be dependent on spatial and time variables. In this way, we can easily construct an extended source function to fit the recorded data by solving a source matching subproblem; hence, it is less prone to cycle skipping. A novel source focusing annihilator, defined as the distance function from the real source position, is used for penalizing the defocused energy in the extended source function. A close data fit avoiding the cycle-skipping problem effectively makes the new method less likely to suffer from local minima, which does not require extreme low-frequency signals in the data. Numerical experiments confirm that our method can mitigate cycle skipping in FWI and is robust against random noise.

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